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Structured-Based Neural Network Classification of Images Using Wavelet Coefficients

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

Image classification is a challenging problem in organizing a large image database. However, an effective method for such an objective is still under investigation. This paper presents a method based on wavelet for image classification with adaptive processing of data structures. After decomposed by wavelet, the features of an image can be reflected by the wavelet coefficients. Therefore, the nodes of tree representation of images are represented by distribution of histograms of wavelet coefficient projections. 2940 images derived from seven original categories are used in experiments. Half of the images are used for training neural network and the other images used for testing. The classification rate of training set is 90%, and the classification rate of testing set is 87%. The promising results prove the proposed method is very effective and reliable for image classification.

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References

  • Cohen, A., Ryan, R.D.: Wavelets and Multiscale Signal Processing. Chapman & Hall Press, Boca Raton (1995)

    MATH  Google Scholar 

  • Giles, C.L., Gori, M.: Adaptive Processing of Sequences and Data Structures. Springer, Berlin (1998)

    Book  Google Scholar 

  • Tsoi, A.C.: Adaptive Processing of Data Structures: An Expository Overview and Comments. Technical report, Faculty of Informatics, University of Wollongong, Australia (1998)

    Google Scholar 

  • Tsoi, A.C., Hangenbucnher, M.: Adaptive Processing of Data Structures. Keynote Speech. In: Proceedings of Third International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 1999, 2-2 (summary) (1999)

    Google Scholar 

  • Frasconi, P., Gori, M., Sperduti, A.: A General Framework for Adaptive Processing of Data Structures. IEEE Trans. on Neural Networks 9, 768–785 (1998)

    Article  Google Scholar 

  • Sperduti, A., Starita, A.: Supervised Neural Networks for Classification of Structures. IEEE Trans. on Neural Networks 8(3), 714–735 (1997)

    Article  Google Scholar 

  • Goller, C., Kuchler, A.: Learning Task-dependent distributed representations by Back-propagation Through Structure. In: Proc. IEEE Int. Conf. Nerual Networks, pp. 347–352 (1996)

    Google Scholar 

  • Cho, S., Chi, Z., Wang, Z., Siu, W.: An Efficient Learning Algorithm for Adaptive Processing of Data Structure. Neural Processing Letters 17, 175–190 (2003)

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong

    Weibao Zou, King Chuen Lo & Zheru Chi

Authors
  1. Weibao Zou
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  2. King Chuen Lo
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  3. Zheru Chi
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Zou, W., Lo, K.C., Chi, Z. (2006). Structured-Based Neural Network Classification of Images Using Wavelet Coefficients. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_48

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  • DOI: https://doi.org/10.1007/11760023_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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